Latest AI and machine learning research in universal precautions for healthcare professionals.
We introduce Alterbute, a diffusion-based method for editing an object's intrinsic attributes in an image. We allow changing color, texture, material, and even the shape of an object, while preserving its perceived identity and scene context. Existing approaches either rely on unsupervised priors that often fail to preserve identity or use overly restrictive supervision that prevents meaningful in...
BackgroundSystemic infections are a leading cause of hospitalization and death among patients with cirrhosis. Timely and accurate infection identification is essential for both clinical care and the development of predictive models. However, existing methods such as ICD-10 coding are unreliable, and manual chart review is resource-intensive and difficult to scale. This study aimed to develop and v...
Medical imaging datasets often suffer from class imbalance and limited availability of pathology-rich cases, which constrains the performance of machi...
The shortage in early detection methods for the pathogen Burkholderia gladioli pv. cocovenenans (BGC) and its toxin bongkrekic acid rises the risk for...
Referring Video Object Segmentation (RVOS) addresses the task of segmenting target objects described by textual descriptions from videos. In order to ...
Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the ...
The increasing global reliance on aquaculture is challenged by disease outbreaks, exacerbated by antibiotic resistance, and environmental stressors. T...
In-context learning (ICL) is emerging as a promising technique for achieving universal medical image segmentation, where a variety of objects of int...
Class-incremental/Continual image segmentation (CIS) aims to train an image segmenter in stages, where the set of available categories differs at ea...
The development of robust deep learning models for breast ultrasound (BUS) image analysis is significantly constrained by the scarcity of expert-ann...
Local motion blur in digital images originates from the relative motion between dynamic objects and static imaging systems during exposure. Existing...
Robust 6D object pose estimation in cluttered or occluded conditions using monocular RGB images remains a challenging task. One reason is that curre...
Video-to-audio (V2A) generation shows great potential in fields such as film production. Despite significant advances, current V2A methods, which re...
Birds' Eye View (BEV) semantic segmentation is an indispensable perception task in end-to-end autonomous driving systems. Unsupervised and semi-supe...
We present 3D PixBrush, a method for performing image-driven edits of local regions on 3D meshes. 3D PixBrush predicts a localization mask and a syn...
To advance real-world fashion image editing, we analyze existing two-stage pipelines(mask generation followed by diffusion-based editing)which overl...
Document shadow removal is a crucial task in the field of document image enhancement. However, existing methods tend to remove shadows with constant...
Dual-mode sensors capable of detecting multiple physical stimuli simultaneously offer significant advantages for advanced applications in human-machin...
We introduce and validate the lottery codec hypothesis, which states that untrained subnetworks within randomly initialized networks can serve as sy...
HIV epidemiological data is increasingly complex, requiring advanced computation for accurate cluster detection and forecasting. We employed quantum...